Dissecting the effect of long-term exposure to air pollution on risk of dementia in UK Biobank

Ensor Rafael Palacios, Chin Yang Shapland, Levi John Wolf, Liv Tybjaerg Nordestgaard, Emma Anderson, Chloe Slaney, Dan Bernie, Dann Mitchell, Patrick Gavin Kehoe, Gareth John Griffith, Kate Tilling

Research output: Working paper / PreprintPreprint

Abstract

Mounting evidence links air pollution to dementia, the most prevalent cause of cognitive impairment in older people. Here we investigated individual and compound effects of particulate matters (PM10, PM2.5, PMcoarse, PMabs) and nitric oxides (NO2, NO) on risk of all-cause dementia, and its most common subtypes, Alzheimer’s disease (AD) and vascular dementia (VAD), using data from UK Biobank. We addressed factors that hinder causal interpretation of associations previously shown in the literature and their translation into clear public health policies. Specifically: 1) spatial confounding by area-level covariates, 2) collinearity among and identification of the most relevant air pollutants, and 3) the time window for pollution exposure. Furthermore, we used chronic obstructive pulmonary disease (COPD) and frequency of oily fish intake in positive and negative control analyses. We found NO2 to be the strongest risk factor for dementia, especially when considering longer periods (≥ 5 years) of exposure (all-cause dementia hazard ratio HR=1.06, 1.02-1.11 per 9.86 µg/m3 interquartile range). There was stronger evidence of an effect on risk for AD than VAD. Positive control analysis did not provide any evidence against causality, although the analyses of spatial confounding and negative control analyses revealed the presence of some residual bias, thus warranting care in the interpretation of the results. Together, our results highlight that targeting air pollution, in particular NO2 levels, could inform preventive public health policies for dementia.
Original languageEnglish
PublishermedRxiv
DOIs
Publication statusPublished - 18 Jun 2025

Funding

E.R.P. was funded by the Wellcome Trust Neural Dynamics PhD studentship (108899/B/15/Z); C.Y.S. is supported by the Medical Research Council Integrative Epidemiology Unit (MC UU 00032/2); L.J.W. had no relevant funding; L.T.N. was funded by the Research Council at the Capital Region of Denmark, Independent Research Fund Denmark grant, Beckett Foundation (10.46540/3100-00007B); E.A. was funded by a UKRI Future Leaders Fellowship (MR/W011581/1); C.S. was funded by UK Medical Research Council (MRC) grant to GMK (MC UU 00032/06); D.B. was funded under the Strategic Priority Fund for UK Climate Resilience, which is supported by the UKRI Strategic Priorities Fund (co-delivered by the Met Office and NERC on behalf of UKRI partners AHRC, EPSRC and ESRC); D.M. had no relevant funding; P.G.K was supported by a Fellowship from the Sigmund Gestetner Founda- tion; G.J.G is was supported by a MQ Fellowship (MQF22/22) and the MRC IEU (MC UU 00032/1); K.T. was supported by the UK Medical Research Council and the University of Bristol (MC UU 00032/02).

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